The article breaks down the recently leaked source code of Anthropic's Claude Code CLI. It highlights the system's architecture, design choices, and differences from OpenAI's Codex, particularly in handling context overflow and user interactions. Key features like compaction strategies and internal versus external user instructions are explored.

This article introduces the Codex Plugin for Claude Code, explaining its functions and setup requirements. It highlights key commands for running reviews and managing tasks, emphasizing how it integrates seamlessly into existing workflows.

The article analyzes the latest coding models, Opus 4.6 and Codex 5.3, highlighting their usability and performance differences. Codex 5.3 shows significant improvements over its predecessors, but still lags behind Claude in user-friendliness and overall experience. The discussion also touches on the shifting importance of benchmarks in evaluating AI models.

This article explains the Codex agent loop, which is the mechanism that allows the Codex CLI to interact with users and perform software tasks. It details how user input is processed, how queries are sent to the model, and how responses are generated, including tool calls for executing commands.

This article explains how to implement Claude Skills in Codex using a simple enumerator script. It outlines the setup process for both project-level and global skill management, allowing for easy access and updates across multiple repositories. The focus is on maintaining a vendor-agnostic approach while ensuring efficient skill discovery and use.

This article covers several recent updates to OpenAI's Codex and Responses API. Key highlights include the introduction of skills for Codex, new multi-provider support, and enhancements like Gmail and Google Calendar integration. The updates aim to improve usability and efficiency for developers.

OpenAI has implemented a new "skills" feature in ChatGPT and Codex CLI, allowing users to access and utilize structured resources for tasks like document creation. The skills function by organizing Markdown files and additional resources in a specific folder, enabling tasks such as generating PDFs and creating plugins. This development mirrors similar features from Anthropic, indicating a growing trend in AI tool capabilities.

This article covers a podcast episode with OpenAI's Alexander Embiricos, who discusses how to effectively use Codex for coding tasks. It highlights workflows, the importance of structured planning, and how the latest GPT-5.2 model improves efficiency. Key takeaways include the significance of human judgment and the integration of AI tools into existing workflows.

This article discusses how OpenAI leverages Codex to improve the effectiveness of agents in handling complex tasks. It highlights the importance of context management, the organization of documentation, and the need for a structured repository to enhance agent performance. Key lessons include avoiding overwhelming instructions and ensuring that all relevant knowledge is accessible to agents.

This article discusses a Reddit AMA with the Codex team, where they answer questions about Codex, their coding agent. The session highlights recent upgrades, including the launch of the gpt-5-codex model. It provides a schedule for the live Q&A and lists team members participating.

OpenAI CEO Sam Altman announced that ChatGPT is experiencing over 10% monthly growth again, despite competition from Anthropic. The company plans to launch an updated Chat model soon and is testing ads within ChatGPT. OpenAI is also in discussions for a potential $100 billion funding round to support its expanding operations.

This article outlines how the Sora Android app was developed in just 28 days using Codex. It discusses the challenges and advantages of integrating Codex into the engineering workflow, emphasizing the importance of clear guidance and context for effective collaboration.

OpenAI has launched GPT-5.3-Codex-Spark, a new model focused on real-time coding with ultra-low latency. It features a 128k context window and is designed for interactive tasks, allowing developers to make immediate edits and receive quick responses. This model will help improve coding workflows and is available to ChatGPT Pro users for experimentation.

This article outlines the capabilities of GPT-5.3-Codex, highlighting improvements in web development and support for various software lifecycle tasks. It also discusses enhanced cybersecurity features and the model's ability to engage interactively with users.

This article provides guidance on optimizing the Codex model for coding tasks using the API. It covers recommended practices for prompting, tool usage, and code implementation to enhance performance and ensure efficient task completion.

OpenAI announced several updates, including Open Responses, an open-source spec for building multi-provider LLM interfaces. The introduction of GPT-5.2-Codex enhances complex coding tasks, while new skills and connectors improve usability and integration with other platforms.

The article details the author's process of reverse engineering the Codex CLI tool to access the newly released GPT-5-Codex-Mini model. By modifying the tool, they created a command to generate SVGs based on user prompts, specifically focusing on drawing a pelican riding a bicycle. The author shares insights into the coding challenges and the functionality of the modified tool.

This article walks you through creating an MCP server using Semaphore's API. It covers setting up the project, coding the server, and integrating it with tools like OpenAI's Codex for conversational CI/CD interactions.

The Codex app transforms how developers interact with AI agents, enabling them to manage multiple tasks and collaborate effectively. It offers new skills that extend beyond code generation, allowing Codex to perform a variety of tasks on a computer. Developers can customize their interactions with Codex, choosing between a direct or conversational style.

This article explains the architecture and functionality of the Codex App Server, which powers various Codex applications. It details the agent loop, conversation primitives, and how developers can integrate Codex into their products effectively.

This article outlines recent enhancements to the GPT-5.2-Codex model, focusing on its ability to handle complex tasks, support for reusable skills, and new API capabilities. It details improvements in usage limits and integration with various platforms like Gmail and Google Calendar.

The article discusses the differences between Codex and Claude Code, two AI coding tools, highlighting their respective strengths and user preferences. It emphasizes that the choice between them should reflect individual working styles rather than a one-size-fits-all solution. The author encourages experimenting with both tools to find the best fit.

OpenAI has released GPT-5.2-Codex, an advanced coding model designed for software development and cybersecurity. It enhances long-context understanding, tool reliability, and cybersecurity capabilities, enabling more effective coding and threat detection. The release aims to balance accessibility with safety in deployment.

OpenAI's new Codex app for Mac reached over 1 million downloads in its first week, showcasing significant user interest in AI-assisted coding. However, CEO Sam Altman indicated that the app will transition to stricter limits for free and low-cost users after a promotional period.

OpenAI has released a macOS app for Codex, its coding agent, enhancing the user interface and adding features like Skills and Automations. While current Automations can only run on a powered laptop, cloud support is on the way. The app aims to expand Codex's capabilities beyond coding to broader knowledge work tasks.

OpenAI is rolling out a new model called GPT-5.2-Codex-Max for subscribers, which enhances the capabilities of its Codex tool. This version improves performance on long tasks, tool use reliability, and understanding of visual content, building on the features introduced in GPT-5.2. Further details about the model are expected to be released soon.

OpenAI has launched GPT-5.1-Codex-Max, an advanced coding model designed for agentic tasks, which enhances performance in software engineering, debugging, and multi-tasking over extended periods. It features improved token efficiency and the ability to handle complex workflows, making it a powerful tool for developers. The model is now available in Codex, with API access coming soon.

OpenAI has released an upgraded version of Codex powered by the new GPT-5 model, enhancing its capabilities in code generation and understanding. The improvements aim to make the AI more efficient and accurate in assisting developers with programming tasks. This upgrade reflects OpenAI's ongoing commitment to advancing AI technology for practical applications in software development.

OpenAI has introduced significant upgrades to Codex, making it faster and more reliable for developers. The new GPT-5-Codex is optimized for real-world coding tasks, enhancing collaboration and code review capabilities while integrating seamlessly with various development environments.

Codex has introduced several new features including a new extension for popular development tools, an improved CLI for local environments, and enhanced task management capabilities that integrate local and cloud tasks. The updates, which leverage GPT-5, also include support for Codex-driven code reviews in GitHub, marking a significant advancement in developer productivity.

Codex CLI is a local coding agent from OpenAI that can be installed using npm or Homebrew. Users can run Codex after installation and sign in with their ChatGPT account for enhanced functionality. The tool supports various platforms and offers configuration options to tailor user experience.

The author compares three coding agents: Codex, Claude Code, and Cursor, highlighting their similarities and differences in features, pricing, and user experiences. While each has its strengths, the author ultimately prefers Codex for its pricing, GitHub integration, and overall consistency, though acknowledges that user preferences vary widely among the tools.

The article discusses the application of AI research utilizing Codex, a powerful model for code generation and understanding. It highlights various use cases, including improving programming efficiency and enabling new ways of interacting with code through natural language queries. The potential implications for developers and the programming community are also examined.

Codex CLI is transitioning to a native version written in Rust to improve cross-platform stability, performance, and security. The new version aims to reduce dependencies, enhance extensibility, and maintain feature parity with the TypeScript implementation. Feedback from the community continues to shape ongoing development, with an invitation for contributors to join the effort.

OpenAI has launched Codex, a coding tool designed for developers to delegate simple programming tasks to an AI agent that generates production-ready code. Accessible via the ChatGPT web app, Codex operates within a user’s development environment and can be customized through an “AGENTS.md” file for improved effectiveness. Built on a fine-tuned model, Codex leverages reinforcement learning to enhance its coding capabilities.

Codex is a cloud-based software engineering agent designed to assist developers by performing tasks such as writing features, fixing bugs, and generating pull requests in parallel. Available to various user tiers, it prioritizes security and transparency, ensuring users can validate outputs while mitigating risks associated with AI misuse. Early adopters like Cisco and Temporal have successfully integrated Codex into their workflows to enhance productivity and streamline development processes.

The article delves into a comparative analysis of OpenAI's Codex and Anthropic's Claude Code, focusing on their capabilities in code generation and natural language understanding. It evaluates their performance through various coding tasks and highlights the strengths and weaknesses of each model.

Researchers John Justeson and Justin Lowry investigate the design and historical significance of the Mayan eclipse table found in the Dresden Codex. Their study reveals insights into the astronomical knowledge and cultural practices of the Maya civilization, highlighting the importance of this ancient manuscript in understanding Mayan astronomy.